A New Era of Risk

AI agents are moving from experimental pilots to enterprise-scale deployments at remarkable speed. These autonomous systems don’t just analyze data — they retrieve information, call APIs, execute code, and orchestrate workflows across multiple business applications. For enterprises, this means faster innovation, but also a dramatic expansion of the attack surface.

The recent Salesforce-Salesloft-Drift breach is a case in point. While attackers exploited an AI chatbot, the real root of the problem was the rush to roll out AI tools without adequate controls. Agents were given overly broad access to sensitive systems, and when compromised, the breach rapidly spiraled outward — impacting hundreds of companies in a matter of days. It was a powerful reminder that without runtime protection and governance, the scale and speed of AI adoption can magnify risk across the entire enterprise ecosystem.

Why AI Agents Raise the Stakes

AI agents represent a fundamental shift. Unlike chatbots or static applications, agents act autonomously, linking together multiple systems through protocols like MCP. This power accelerates business outcomes — but it also amplifies risks.

As Gartner’s Avivah Litan warns:

“Agentic AI expands the attack and risk surface for enterprises due to the autonomous nature of AI agents, potentially unsafe emergent behaviors and supply chain risks via data retrieval, function calling, code execution or tool usage.”

These risks include:

• Unpredictable behaviors that static testing cannot anticipate.
• Overly broad permissions to access sensitive data.
• Unauthorized changes to systems or workflows.
• Compliance violations when regulated data is mishandled.
• Supply chain vulnerabilities through third-party connectors and plugins.

Enterprises Can’t Afford to Wait

Every major enterprise is building or deploying AI agents to stay competitive. Sales organizations are automating prospecting, operations teams are streamlining workflows, and IT groups are embedding AI into DevOps. The urgency is clear: those who fail to innovate risk being left behind.

But this momentum carries hidden dangers. As the Salesforce-Salesloft-Drift breach demonstrated, attackers already see AI agents as prime targets. Enterprises that rush ahead without guardrails risk exposing critical data, systems, and reputations.

Enabling AI, Not Blocking It

Blocking agent adoption is not a viable option. Enterprises need AI to compete, and employees will continue to find ways to use these technologies. The challenge is not whether to use agents, but how to adopt them safely.

PointGuard AI’s mission has always been about enabling innovation — not slowing it down. By embedding protection, governance, and monitoring into the AI lifecycle, we make it possible for enterprises to realize the benefits of AI agents while keeping data and operations secure.

Expanding PointGuard AI to Protect Agents

Our expanded platform brings end-to-end AI security directly to agentic workflows:

• Discovery & Visibility: Automatically maps agent activity, including MCP calls, data sources, and external connectors, so organizations understand exactly what agents are doing and where risks lie.
• Comprehensive Security Controls: Enforces policies to stop unsafe behaviors, block unauthorized actions, and align with regulatory requirements across PCI, HIPAA, GDPR, and more.
• Stress Testing & Red Teaming: Continuously simulates adversarial behaviors and probes agent workflows to uncover vulnerabilities before attackers do.
• Runtime Guardrails & Data Protection: Provides inline monitoring of every agent decision and response, preventing data loss, injection attacks, and compliance violations in real time.
• Governance & Compliance: Generates full records of agent decisions and outcomes, simplifying audits and enabling responsible adoption aligned with standards like ISO 42001 and NIST AI RMF.

The Path Forward

The race to deploy AI agents is accelerating across industries. Yet the risks are already materializing. Enterprises can no longer assume that testing and perimeter security are enough. Protecting AI agents requires continuous runtime protection, visibility, and governance — the capabilities PointGuard AI was built to deliver.

Conclusion

AI agents represent both the next frontier of enterprise automation and the next frontier of cybersecurity risk. Enterprises cannot afford to choose between innovation and safety — they need both.

With PointGuard AI, organizations can embrace agentic AI with confidence, knowing that their systems, data, and customers are protected every step of the way.